There is an interest and need in the art for reliable and robust detection of flying avians. Avian detection systems have many applications, ranging from avian counts, classification and/or identification in a specific geographical location, to deterrence and counter-measure systems for aviation and wind production systems. A common objective of such systems is the replacement of subjective and inaccurate human-based counts with an automated and reliable detection system. This is a reflection that human-based detection of flying avians requires intensive training to be able to properly identify avians and species thereof, is highly labor intensive and is inherently inaccurate.
One specific application of bird detection systems is for wind energy generation. There is concern as to the risk to avians arising from avian-wind turbine collision. One challenge for accurately assessing the risk of wind turbine collision by a flying avian is the difficulty in reliably determining the number of birds and the species of such birds in an area of a turbine or a to-be-located turbine. It is difficult to continuously monitor airspace, and so conventional bird strike fatality searches are conducted using systematic schedules with an attendant estimate of fatalities based on a uniform distribution over time, as explained in “Impacts of Wind Energy Facilities on Wildlife and Wildlife Habitat” Technical Review 07-2. September 2007 (available at: wildlife.org/documents/technical-reviews/docs/Wind07-2.pdf). This has numerous disadvantages, including not accounting for cluster fatalities, injured avians that leave the immediate area or are removed by scavengers, and the challenge associated with reliably and consistently locating carcasses. Regardless of such inaccuracies, there has been documentation of raptor fatalities at wind turbine fatalities. See, e.g., Id. at p. 15 and references cited therein, including for California-based wind-farm facilities such as the Altamont Pass Wind Resource Areas (APWRA), San Goronio and Tehachapi. Estimates for raptor kills at APWRA per year range from between 881-1300 or about 1.5-2.2 raptor fatalities/MW/year, including about 75 to 116 Golden Eagles. With these statistics in mind, there is interest in bird detection systems including for use with wind-farm planning, development, expansion and operation.
One example of a bird detection and dissuasion system is dtbird® by Liquen (description available at dtbird.com/index.php/en/technology/detection). A fundamental limitation of that system is the reported detection efficiency of 86-96% for a distance of only 150 m from the wind turbine, with an efficiency that falls off with increasing distances.
Other implementations of avian detection systems are based on radar including, for example, Merlin Avian Radar Systems by DeTect (www.detect-inc.com/avian.html). Those systems, however, require bulky and expensive radar equipment and are not suited to distinguishing between avian species of interest. For example, a fundamental drawback is the inability to distinguish between an endangered or valued raptor species and another bird species that is neither endangered or of commercial importance. For example, it would be beneficial to distinguish between a golden eagle and a turkey vulture, for example with action implementation for wind blade speed tailored to species of interest only. Radar systems are not suited for such applications, as they do not obtain visual details that would otherwise distinguish between different bird species that are similarly sized and/or have similar flight characteristics. Furthermore, radar-based systems produce many false-positives, including arising from moving objects such as a turbine blade.
U.S. Pat. Pub. 2013/0050400 (Stiesdal) describes an arrangement to prevent collision of a flying animal with a wind turbine. Stiesdal, however, is limited in that there is not full spatial coverage, but instead focuses on imaging horizontal directions. U.S. Pat. No. 8,598,998 describes an animal collision avoidance system. Other systems are described, for example, in U.S. Pat. Pub. Nos. 2009/0185900 (Hirakata) and 2008/0298692 (Silwa). Each of those systems have inherent limitations, such as not providing full coverage of all directions of the surrounding airspace, do not provide sufficient detection efficiency and/or cannot reliably distinguish between avian species and confine detection to a specific avian species.
Because of the risk to migratory birds, raptors and other avians of interest including bats, it is desirable to have a reliable, cost-effective and robust system for identifying certain avian species, including before siting of wind turbine(s) as well as during wind turbine operation. Provided herein are various methods and systems for avian detection, including highly reliable and sensitive detection systems over sufficiently large detection ranges that provide sufficient time to take action to minimize or avoid unwanted contact between a specific avian species and the wind turbine, while minimizing unnecessary wind turbine shutdown for avian species or other moving objects that are not of interest, while avoiding the need for large groups of human observers.